from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 14.0 | 33.307833 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 26.047819 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 35.520019 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 45.018181 |
| KMeans_tall | 0.0 | 1.0 | 48.418566 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 17.846428 |
| KMeans_short | 0.0 | 0.0 | 26.676209 |
| daal4py_KMeans_short | 0.0 | 0.0 | 13.397495 |
| LogisticRegression | 0.0 | 1.0 | 10.559725 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 2.411753 |
| Ridge | 0.0 | 1.0 | 1.396874 |
| daal4py_Ridge | 0.0 | 0.0 | 23.457970 |
| total | 0.0 | 35.0 | 44.147974 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.170 | 0.009 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.643 | 0.064 | 0.265 | 0.030 | See |
| 1 | KNeighborsClassifier | predict | 0.268 | 0.017 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 0.200 | 0.030 | 1.340 | 0.221 | See |
| 2 | KNeighborsClassifier | predict | 34.485 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 4.416 | 0.115 | 7.809 | 0.203 | See |
| 3 | KNeighborsClassifier | fit | 0.155 | 0.006 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.661 | 0.052 | 0.234 | 0.021 | See |
| 4 | KNeighborsClassifier | predict | 0.256 | 0.013 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.176 | 0.021 | 1.454 | 0.187 | See |
| 5 | KNeighborsClassifier | predict | 40.868 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 4.138 | 0.157 | 9.876 | 0.376 | See |
| 6 | KNeighborsClassifier | fit | 0.147 | 0.011 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.504 | 0.015 | 0.292 | 0.023 | See |
| 7 | KNeighborsClassifier | predict | 0.211 | 0.009 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.110 | 0.004 | 1.921 | 0.110 | See |
| 8 | KNeighborsClassifier | predict | 41.192 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 4.000 | 0.043 | 10.299 | 0.110 | See |
| 9 | KNeighborsClassifier | fit | 0.129 | 0.004 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.513 | 0.011 | 0.250 | 0.010 | See |
| 10 | KNeighborsClassifier | predict | 0.195 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 0.108 | 0.004 | 1.803 | 0.078 | See |
| 11 | KNeighborsClassifier | predict | 17.570 | 0.654 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 3.882 | 0.029 | 4.526 | 0.172 | See |
| 12 | KNeighborsClassifier | fit | 0.151 | 0.017 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.511 | 0.020 | 0.295 | 0.035 | See |
| 13 | KNeighborsClassifier | predict | 0.245 | 0.027 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.098 | 0.002 | 2.498 | 0.281 | See |
| 14 | KNeighborsClassifier | predict | 25.424 | 0.056 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 3.943 | 0.065 | 6.448 | 0.107 | See |
| 15 | KNeighborsClassifier | fit | 0.129 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.512 | 0.016 | 0.251 | 0.009 | See |
| 16 | KNeighborsClassifier | predict | 0.214 | 0.007 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.103 | 0.002 | 2.068 | 0.078 | See |
| 17 | KNeighborsClassifier | predict | 26.165 | 0.428 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 3.983 | 0.069 | 6.569 | 0.156 | See |
| 18 | KNeighborsClassifier | fit | 0.059 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.104 | 0.004 | 0.567 | 0.029 | See |
| 19 | KNeighborsClassifier | predict | 0.021 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 4.747 | 0.633 | See |
| 20 | KNeighborsClassifier | predict | 25.565 | 0.008 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.809 | 0.015 | 31.590 | 0.571 | See |
| 21 | KNeighborsClassifier | fit | 0.063 | 0.003 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.105 | 0.004 | 0.601 | 0.032 | See |
| 22 | KNeighborsClassifier | predict | 0.029 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.004 | 0.000 | 6.475 | 0.625 | See |
| 23 | KNeighborsClassifier | predict | 34.460 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.820 | 0.015 | 42.049 | 0.762 | See |
| 24 | KNeighborsClassifier | fit | 0.062 | 0.003 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.106 | 0.004 | 0.585 | 0.038 | See |
| 25 | KNeighborsClassifier | predict | 0.029 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.005 | 0.000 | 6.277 | 0.714 | See |
| 26 | KNeighborsClassifier | predict | 33.844 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.885 | 0.023 | 38.263 | 0.992 | See |
| 27 | KNeighborsClassifier | fit | 0.061 | 0.003 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.105 | 0.002 | 0.579 | 0.029 | See |
| 28 | KNeighborsClassifier | predict | 0.015 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.004 | 0.000 | 3.448 | 0.365 | See |
| 29 | KNeighborsClassifier | predict | 11.652 | 0.277 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.814 | 0.014 | 14.315 | 0.422 | See |
| 30 | KNeighborsClassifier | fit | 0.060 | 0.003 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.104 | 0.002 | 0.577 | 0.034 | See |
| 31 | KNeighborsClassifier | predict | 0.022 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.004 | 0.000 | 4.947 | 0.450 | See |
| 32 | KNeighborsClassifier | predict | 20.110 | 0.331 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.808 | 0.008 | 24.902 | 0.471 | See |
| 33 | KNeighborsClassifier | fit | 0.059 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.105 | 0.004 | 0.560 | 0.023 | See |
| 34 | KNeighborsClassifier | predict | 0.022 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.004 | 0.000 | 4.911 | 0.566 | See |
| 35 | KNeighborsClassifier | predict | 20.463 | 0.799 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.882 | 0.012 | 23.214 | 0.963 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.868 | 0.045 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.705 | 0.008 | 4.071 | 0.080 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 9.763 | 5.335 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.442 | 0.005 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.117 | 0.002 | 3.776 | 0.083 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.927 | 0.037 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.744 | 0.009 | 3.936 | 0.069 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 8.034 | 3.394 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.889 | 0.015 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.215 | 0.002 | 4.141 | 0.081 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.921 | 0.054 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.712 | 0.014 | 4.104 | 0.112 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.007 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 10.460 | 3.838 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.755 | 0.024 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.649 | 0.010 | 4.242 | 0.074 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.966 | 0.042 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.755 | 0.011 | 3.929 | 0.081 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 3.156 | 2.113 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.806 | 0.013 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.117 | 0.002 | 6.878 | 0.152 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.918 | 0.043 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.702 | 0.009 | 4.156 | 0.080 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 3.831 | 1.963 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.541 | 0.016 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.215 | 0.003 | 7.169 | 0.117 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.919 | 0.048 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.758 | 0.011 | 3.849 | 0.084 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 4.905 | 2.229 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 5.156 | 0.095 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.651 | 0.012 | 7.925 | 0.208 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.358 | 0.023 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.494 | 0.007 | 2.748 | 0.063 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 7.482 | 4.650 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.036 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 39.804 | 18.182 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.311 | 0.035 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.498 | 0.006 | 2.635 | 0.076 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 14.423 | 7.250 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.038 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.002 | 0.001 | 22.607 | 8.818 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.298 | 0.016 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.500 | 0.015 | 2.594 | 0.082 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 12.290 | 6.141 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.059 | 0.004 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 7.861 | 1.018 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.274 | 0.013 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.506 | 0.012 | 2.518 | 0.066 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 4.650 | 2.977 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.032 | 0.002 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.001 | 33.869 | 19.025 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.272 | 0.012 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.507 | 0.009 | 2.512 | 0.050 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 4.654 | 3.743 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.034 | 0.002 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 28.440 | 6.481 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.278 | 0.017 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.506 | 0.008 | 2.525 | 0.054 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 4.912 | 2.596 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.063 | 0.003 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 8.829 | 1.040 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.638 | 0.007 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.321 | 0.008 | 1.989 | 0.052 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.018 | 1.152 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.943 | 1.006 | See |
| 3 | KMeans_tall | fit | 0.546 | 0.008 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.284 | 0.006 | 1.923 | 0.052 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.380 | 1.279 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.736 | 0.821 | See |
| 6 | KMeans_tall | fit | 7.432 | 0.067 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.977 | 0.043 | 1.869 | 0.026 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.093 | 1.139 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.526 | 1.321 | See |
| 9 | KMeans_tall | fit | 6.788 | 0.005 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.763 | 0.036 | 1.804 | 0.017 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.233 | 0.928 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.749 | 0.865 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.390 | 0.010 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 26.0 | NaN | 30.0 | NaN | 0.155 | 0.009 | 2.525 | 0.156 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 0.903 | 0.531 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.257 | 0.682 | See |
| 3 | KMeans_short | fit | 0.146 | 0.005 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.074 | 0.005 | 1.984 | 0.151 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.161 | 1.022 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.593 | 0.561 | See |
| 6 | KMeans_short | fit | 1.311 | 0.055 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 21.0 | NaN | 21.0 | NaN | 0.610 | 0.036 | 2.150 | 0.157 | See |
| 7 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.302 | 0.770 | See |
| 8 | KMeans_short | predict | 0.008 | 0.003 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 5.574 | 2.236 | See |
| 9 | KMeans_short | fit | 0.367 | 0.062 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 23.0 | NaN | 22.0 | NaN | 0.324 | 0.039 | 1.130 | 0.234 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.076 | 1.076 | See |
| 11 | KMeans_short | predict | 0.004 | 0.002 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.001 | 1.729 | 1.084 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 15.740 | 0.096 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 15.715 | 0.064 | 1.002 | 0.007 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.318 | 0.286 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.909 | 0.430 | See |
| 3 | LogisticRegression | fit | 1.205 | 0.016 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 1.236 | 0.021 | 0.974 | 0.021 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.000 | 0.132 | 0.078 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.005 | 0.001 | 0.522 | 0.183 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 2.675 | 0.040 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 1.556 | 0.019 | 1.719 | 0.033 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.253 | 0.180 | See |
| 2 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.001 | 0.000 | 0.661 | 0.274 | See |
| 3 | Ridge | fit | 1.419 | 0.017 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.332 | 0.005 | 4.276 | 0.084 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.352 | 0.310 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.591 | 0.328 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.12.so",
"prefix": "libopenblas",
"user_api": "blas",
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"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}